汽车客户售后服务项目个性化推荐研究
[Abstract]:With China entering the automobile society, more and more attention has been paid to the development of automobile service industry. In recent years, more and more families have owned automobile, and the consumption structure of automobile in our country has changed greatly. Automobile enterprises gradually realize the importance of automobile after-sales service to strengthen customer relationship and improve customer satisfaction. However, due to the late start of automobile industry in China, the level of after-sales service is still in the primary stage of development, and there is a huge gap between China and developed countries in every link. The development of automobile after-sales service market is slow, which to some extent affects the development of automobile industry in our country. In the automobile market, service is a very important part of the whole marketing market. Automobile after-sales service market must reach the goal of serving customer demand, only then can enhance its own level. Different from other commodities, the consumption of various services produced by the automobile after purchase is continuous and diversified, and the consumption of these services accounts for a significant proportion of the total consumption of the automobile. Automobile after-sales service projects involve a wide range of initiative to provide personalized service items for customers to recommend can help improve customer satisfaction increase customer loyalty enhance the competitiveness of enterprises. According to customer's new and old degree, this article carries on the automobile after-sale service project recommendation separately. On the basis of data mining and service recommendation, combined with graph theory knowledge, community network and bipartite graph model are used to subdivide customers and recommend service items. To study the personalized service recommendation method between similar customers. The main research contents of this paper are as follows: firstly, this paper analyzes the automobile after-sales service and community network by consulting relevant domestic and foreign literature. The theoretical knowledge and research status of bipartite graph matching and service recommendation. Secondly, this paper uses association mining algorithm to subdivide the old customers, divide the customer groups with similar consumption behavior, and construct a bipartite graph model to recommend the service items. For new customers, the problem that service mining can not be done through a large amount of history is studied. The demographic characteristics are introduced, and the calculation formula of customer similarity is constructed to find out the old customers with high similarity to customers. And combined with the trend of service selection to the new customer personalized service recommendation. Finally, based on the customer data of automobile 4S store, this paper analyzes and verifies the recommended method of automobile after-sales service project through supplement and simulation. Based on the different research of new and old customers, the customer group is divided into different individuals, and according to its differentiation, auto repair and maintenance services, auto beauty services, auto insurance services and other additional services are provided selectively. The service items are subdivided to enable customers to enjoy appropriate services and meticulous care, to improve customer relations and service quality.
【学位授予单位】:武汉理工大学
【学位级别】:硕士
【学位授予年份】:2013
【分类号】:F274;F426.471
【参考文献】
相关期刊论文 前10条
1 裘江南;仲秋雁;崔彦;;服务匹配模型中综合语义匹配方法研究[J];大连理工大学学报;2007年06期
2 刘小艳;刘欣宇;王梅;;隶属函数的确定及应用[J];电脑知识与技术;2010年31期
3 阎长顺;李一军;;基于云模型的动态客户细分分类模型研究[J];哈尔滨工业大学学报;2007年02期
4 刘文远;张庆大;王宝文;石岩;;一种基于核集与相似性的模糊推理方法[J];计算机科学;2008年02期
5 邓水光;尹建伟;李莹;吴健;吴朝晖;;基于二分图匹配的语义Web服务发现方法[J];计算机学报;2008年08期
6 牛强;夏士雄;胡祖辉;;基于二分图的故障规则匹配优化算法[J];控制与决策;2011年08期
7 金会庆;宋扬;张维一;陆汝占;郭华;王卫;;本体映射的方法在汽车领域的应用[J];计算机工程与设计;2008年16期
8 于宽春;赵yN;姚青;;满足客户个性化需求的服务匹配算法[J];计算机工程与设计;2009年24期
9 孙林;吴相林;罗松涛;周莉;张红艳;;基于二分图资源分配动力学的推荐排序研究[J];计算机工程与设计;2010年23期
10 王虎;毛文婷;;基于云模型的电信客户行为关联规则研究[J];武汉理工大学学报(信息与管理工程版);2009年05期
相关博士学位论文 前2条
1 李增芳;基于人工智能和虚拟仪器技术的发动机故障诊断专家系统研究[D];浙江大学;2004年
2 肖辉;时间序列的相似性查询与异常检测[D];复旦大学;2005年
相关硕士学位论文 前9条
1 方吉辰;供应链环境下的汽车服务绩效评价体系研究[D];山东大学;2011年
2 王飞;基于隶属函数特征参数相似性的模糊推理方法[D];西南交通大学;2011年
3 姚芳斌;国际职业标准分类体系更新及与中国的比较[D];东北财经大学;2011年
4 何峰;二分图顶点覆盖问题的求解及应用[D];昆明理工大学;2002年
5 邢留伟;K-Means算法在客户细分中的应用研究[D];西南财经大学;2007年
6 梁凤凤;基于本体的分布式语义Web服务发现研究[D];北京邮电大学;2008年
7 王保义;客户关系管理中客户细分的数据挖掘研究[D];西安电子科技大学;2009年
8 刘历波;基于用户偏好的汽车售后服务推荐研究[D];武汉理工大学;2010年
9 吕书玉;基于客户行为分析的汽车售后备件损耗关联研究[D];武汉理工大学;2012年
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